Method and system for mobile device localization in extreme ambient conditions

ABSTRACT

A method and system for localizing a mobile device in extreme ambient conditions. The method, executed in a processor of the mobile device, comprises detecting, using a temperature sensor of the mobile device at a first sampling rate, an ambient temperature anomaly along an indoor route being traversed, determining, based on switching to a second sampling rate, that the ambient temperature anomaly persists over a sequence of positions along the indoor route, filtering a set of barometric ambient pressure measurements contemporaneously associated with the sequence of positions, the set obtained using a barometric pressure sensor of the mobile device, and localizing the mobile device based at least partly on the filtered set of barometric ambient pressure measurements.

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority to U.S. application Ser.No. 16/101826 filed 13 Aug. 2018, which is hereby incorporated in theentirety herein.

TECHNICAL FIELD

The disclosure herein relates to the field of mobile device navigationand positioning.

BACKGROUND

Users of mobile devices are increasingly using and depending upon indoorpositioning and navigation applications and features. Seamless, accurateand dependable indoor positioning of a mobile device as carried or wornby a user can be difficult to achieve using satellite-based navigationsystems when the latter becomes unavailable, or sporadically available,and therefore unreliable, such as within enclosed or partially enclosedurban infrastructure and buildings, including hospitals, shopping malls,airports, universities and industrial warehouses. Barometric ambientmeasurements, in addition to wireless signal and inertial measurements,may be used to localize a mobile device within a multi-floor build beingtraversed. Barometric pressure data, however, may be subject tospurious, and therefore undependable, correlations with height oraltitude under certain extreme ambient conditions.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates, in an example embodiment, a system for localizing amobile device.

FIG. 2 illustrates, in one example embodiment, an architecture of amobile device including localization capability for extreme ambientconditions.

FIG. 3 illustrates, in one example embodiment, variations in barometricpressure with temperature considerations for localizing a mobile devicein extreme ambient temperature conditions.

FIG. 4 illustrates, in an example embodiment, a method of localizing amobile device based on extreme ambient temperature conditions.

DETAILED DESCRIPTION

Embodiments herein provide for localizing a position of a mobile deviceat least in part based on ambient barometric pressure measurements. Theinventors herein recognize that barometric pressure data, however, maybe subject to spurious and undependable correlations with height andbuilding floor number under certain extreme ambient temperatureconditions. Among other benefits and technical effects, it is recognizedthat such spurious barometric ambient pressure data may be filtered inorder to maintain integrity of floor identification as localized for acarried mobile device in extreme temperature conditions, such as forfirefighters or similar rescue personnel.

Provided is a method for localizing a mobile device in extreme ambientconditions. The method, executed in a processor of the mobile device,comprises detecting, using a temperature sensor of the mobile device ata first sampling rate, an ambient temperature anomaly along an indoorroute being traversed, determining, based on switching to a secondsampling rate, that the ambient temperature anomaly persists over asequence of positions along the indoor route, filtering a set ofbarometric ambient pressure measurements contemporaneously associatedwith the sequence of positions, the set obtained using a barometricpressure sensor of the mobile device, and localizing the mobile devicebased at least partly on the filtered set of barometric ambient pressuremeasurements.

Also provided is a mobile device including a processor and a memorystoring a set of computer instructions. The instructions are executablein the processor to detect, using a temperature sensor of the mobiledevice at a first sampling rate, an ambient temperature anomaly along anindoor route being traversed, determine, based on switching to a secondsampling rate, that the ambient temperature anomaly persists over asequence of positions along the indoor route, filter a set of barometricambient pressure measurements contemporaneously associated with thesequence of positions, the set obtained using a barometric pressuresensor of the mobile device, and localize the mobile device based atleast partly on the filtered set of barometric ambient pressuremeasurements.

One or more embodiments described herein provide that methods,techniques, and actions performed by a computing device are performedprogrammatically, or as a computer-implemented method. Programmatically,as used herein, means through the use of code or computer-executableinstructions. These instructions can be stored in one or more memoryresources of the computing device. A programmatically performed step mayor may not be automatic.

One or more embodiments described herein can be implemented usingprogrammatic modules, engines, or components. A programmatic module,engine, or component can include a program, a sub-routine, a portion ofa program, or a software component or a hardware component capable ofperforming one or more stated tasks or functions. As used herein, amodule or component can exist on a hardware component independently ofother modules or components. Alternatively, a module or component can bea shared element or process of other modules, programs or machines.

A mobile device as described herein may be implemented, in whole or inpart, on mobile computing devices such as cellular or smartphones,laptop computers, wearable computer devices, and tablet devices. Memory,processing, and network resources may all be used in connection with theuse and performance of embodiments described herein, including with theperformance of any method or with the implementation of any system.

Furthermore, one or more embodiments described herein may be implementedthrough the use of logic instructions that are executable by one or moreprocessors. These instructions may be carried on a computer-readablemedium. In particular, machines shown with embodiments herein includeprocessor(s) and various forms of memory for storing data andinstructions. Examples of computer-readable mediums and computer storagemediums include portable memory storage units, and flash memory (such ascarried on smartphones). A mobile device as described herein utilizesprocessors, memory, and logic instructions stored on computer-readablemedium. Embodiments described herein may be implemented in the form ofcomputer processor-executable logic instructions or programs stored oncomputer memory mediums.

System Description

FIG. 1 illustrates, in an example embodiment, mobile device localizationsystem 100 including mobile device 101. Mobile device 101 may be such asa wearable computing and communication device, a cellular or smartphone,a laptop or a tablet computer that is operational for any one or more oftelephony, messaging, and data computing. Mobile device 101 may beconnected within communication network system 106, including theinternet or other wide area network, to one or more remote servercomputing devices 107. Mobile device 101 may include mobile devicelocalization logic module 105, the latter embodied according to computerprocessor-executable instructions stored within a memory of, orotherwise accessible to a processor of, mobile device 101. In alternateembodiments, it is contemplated that one or more portions of mobiledevice localization logic module 105 may be stored at remote servercomputing device 107 and made communicatively accessible to mobiledevice 101 via communication network 106.

A navigation, or positioning, software application downloaded andinstalled, or stored, in a memory of mobile device 101 may renderphysical layout map 102 related to a facility or building, including amulti-floor building or indoor facility, within a user interface displayof mobile device 101. In one embodiment, the navigation softwareapplication may incorporate mobile device localization logic module 105.The terms indoor facility or building as used herein means an at leastpartially enclosed building having at least one fixed boundary, such asan exterior boundary wall. Display of physical layout map 102 mayfurther show trajectory or route 103 traversed by the mobile device,which may include an estimated trajectory segment predicted fortraversal by mobile device 101 within a multi-floor building orfacility. Physical layout map 102 may further depict one or more mapconstraint features 104, such as an internal wall or other mapconstraint feature including a doorway, a facility exit, a physicalmarker fixed in place, a facility entrance, a stairwell, a stairway, acorridor, an elevator, and an external boundary outline of themulti-floor indoor facility.

Positioning fingerprint data repository 108 may be communicativelyaccessible to mobile device 101, for instance via communication network106. In alternate embodiments, positioning fingerprint data repository108, or any portion(s) thereof, may be stored in a memory of mobiledevice 101. The terms fingerprint and fingerprint data as used hereinrefer to time-correlated, individual measurements of any of, or anycombination of, received wireless communication signal strength andsignal connectivity parameters, magnetic field parameters or barometricpressure parameters, and mobile device inertial sensor data at known,particular locations along a route being traversed, or anticipated fortraversal, by the mobile device. In other words, a fingerprint includesa correlation of sensor and signal information (including, but notnecessarily limited to wireless signal strength, magnetic or barometricinformation, inertial sensor information) associated for a uniquelocation relative to the facility. Thus, fingerprint data associatedwith a particular location or position provides a signature thatuniquely correlates to that particular location or position. Once aparticular fingerprint or signature based on any of received wirelesscommunication signal strength and signal connectivity parameters,magnetic field parameters or barometric pressure parameters, and mobiledevice inertial sensor data is detected or recorded by mobile device101, the fingerprint as detected may be matched to a referencefingerprint stored in a fingerprint map of a given facility, for exampleas stored in positioning fingerprint data repository 108, to identifythe unique position of the mobile device relative to the facility, aprocess also referred to herein as localization. A sequence of positionsor locations that constitute a navigation path traversed by the mobiledevice relative to the indoor facility may be mapped for fingerprintdata during a fingerprint calibration process. In some embodiments,given that sampling times and sampling rates applied in conjunction withparticular mobile device sensors may be different, the signal and sensorinformation as measured during a fingerprint calibration process may betime-averaged across particular periods of time, with the time-averagedvalue being used to represent the signal information at any giveninstance of time within that particular period of time in which thesignal information is time-averaged. Fingerprint data may be used totrack mobile device 101 traversal along route 103 within, and evenadjoining, the indoor facility.

FIG. 2 illustrates, in one example embodiment, an architecture of mobiledevice 101 including localization capability for extreme ambientconditions. Mobile device 101 may include processor 201, memory 202,display screen 203, input mechanisms 204 such as a keyboard orsoftware-implemented touchscreen input functionality, barcode, QR codeor other symbol- or code-scanner input functionality. Mobile device 101may include sensor functionality by way of sensor devices 205. Sensordevices 205 may include inertial sensors such as an accelerometer and agyroscope, and magnetometer or other magnetic field sensingfunctionality, barometric or other ambient pressure sensors and sensingfunctionality, ambient temperature sensors and temperature sensingfunctionality, ambient gas sensors and ambient lighting sensors. Mobiledevice 101 may also include capability for detecting and communicativelyaccessing ambient wireless communication signals including but notlimited to any of Bluetooth and Bluetooth Low Energy (BLE), Wi-Fi, RFID,and also satellite-based navigations signals including globalpositioning system (GPS) signals. Mobile device 101 further includes thecapability for detecting, via sensor devices 205, and measuring areceived signal strength, and of determining signal connectivityparameters, related to the ambient wireless signals. In particular,mobile device 101 may include location determination capability such asby way of GPS module 206 having a GPS receiver, and communicationinterface 207 for communicatively coupling to communication network 106,including by sending and receiving cellular data over data and voicechannels.

Mobile device localization logic module 105 includes instructions storedin memory 202 of mobile device 101. In embodiments, mobile devicelocalization logic module 105 may be included in a mobile devicenavigation application program stored in memory 202 of mobile device101. The term indoor location as used herein refers to a location withinthe facility or building, such as within a shopping mall, an airport, awarehouse, a university campus, or any at least partially enclosedbuilding. Mobile device localization logic module 105 may comprisesub-modules including temperature anomaly detection module 210, anomalyconfirmation module 211, ambient pressure filtering module 212 andbarometric localization module 213.

Processor 201 uses executable instructions stored in temperature anomalydetection module 210 to detect, using a temperature sensor of mobiledevice 101 operated at a first sampling rate, an ambient temperatureanomaly along indoor route 103 being traversed, such as resulting from abuilding from a fire or high-temperature flames. In embodiments, mobiledevice 101 barometric pressure data may include a set of barometricpressure measurements using one or more barometric pressure sensors ofmobile device 101 while traversing a sequence of positions along route103. Route 103 being traversed may be such as a hallway, a corridor, apedestrian path, a set of stairs or a route commencing from an entranceof a multi-floor facility.

Processor 201 executes instructions included in anomaly confirmationmodule 211 to determine, based on switching to a second sampling rate,that the ambient temperature anomaly persists over a sequence ofpositions along route 103 being traversed. In one embodiment, theambient temperature sampling rate of temperature sensors of mobiledevice 101 may be switched to operate at a higher frequency in order toconfirm, with better certainty, the persistence of high-temperatureflames within a building, for instance.

Processor 201 uses executable instructions stored in ambient pressurefiltering module 212 to filter a set of barometric ambient pressuremeasurements contemporaneously associated with the sequence of positionsalong route 103 during traversal, by mobile device 101, the set ofbarometric ambient pressure measurements obtained using a barometricpressure sensor of the mobile device 101. In one embodiment, where thetemperature anomaly that includes a temperature spike exists over agiven duration of time, a corresponding or contemporaneous barometricpressure anomaly over same duration that includes a barometric ambientpressure spike may be identified. Barometric ambient pressuremeasurements of mobile device 101 may filter the barometric ambientpressure anomaly. A threshold temperature may be predetermined to definewhen an extreme condition temperature anomaly exists. For example, whenthe ambient temperature increases at a rate higher than 3-10 degreesCelsius per minute, in one embodiment.

In one embodiment, the filtering constitutes disregarding ambientbarometric pressure changes as sensed by mobile device 101 for the givenduration of time, as the latter may falsely indicate a height change orfloor change of mobile device 101 when in fact no such change occurred,but rather, the spike in ambient pressure as measured by mobile device101 resulting from presence and persistence of high-temperature flamesor similar extreme ambient temperature anomaly. In this manner ofidentifying a given temperature anomaly along with its respectiveduration, barometric ambient pressure measurements contemporaneous withthat same duration are identified as spurious, disregarded, andtherefore not taken into account in localizing mobile device 101 to aparticular floor of a multi-floor building. In one embodiment, thefiltering at least partially discards pressure measurementscontemporaneous with a duration of the temperature anomaly that exceedsa predetermined threshold temperature for at least a portion of thesequence of positions. In yet another variation, the method may includealgorithmically smoothing the filtered set of barometric ambientpressure measurements, minimizing the effects of noise in the barometricpressure measurements, prior to localizing mobile device 101.

Processor 201 uses executable instructions stored in barometriclocalization module 213 to localize mobile device 101 based at leastpartly on matching the filtered set of barometric ambient pressuremeasurements with barometric fingerprint data of repository 108 alongroute 103. In embodiments, the fingerprint map data stored infingerprint data repository 108 (also referred to herein as repository108) further associates unique positions along route 103 with anycombination of fingerprint data, including gyroscope data, magneticdata, accelerometer data, wireless signal strength data, wirelessconnectivity data, barometric data, acoustic data, line-of sight data,and ambient lighting data, in addition to barometric pressurefingerprint data stored thereon.

FIG. 3 illustrates, in one example embodiment, variations in barometricpressure with temperature considerations for localizing mobile device101 in extreme ambient temperature conditions during traversal along asequence of positions of an indoor facility. It is observed that whilebarometric ambient pressure measurements by mobile device 101 maygenerally, and under normal conditions, indicate a height, altitude orfloor number of a multi-floor building or similar facility, extreme andanomalous temperature conditions, such as experienced in building orfloor engulfed in flames, may generate false or spurious barometricpressure readings. For instance, a higher barometric pressure readingcaused by the higher temperatures spuriously indicating that mobiledevice 101 has transitioned to a lower floor of the building, when infact no such transition occurred.

In particular, FIG. 3 depicts ambient temperature 301 contemporaneouswith ambient barometric pressure 310 while traversing a sequence ofpositions in a floor of a multi-floor building, in one embodiment. Wherethe temperature anomaly that includes temperature spike 301 a existsover duration of time 302 while traversing a portion of sequence ofpositions, such as in the presence of a fire or high-temperature flames,a corresponding barometric pressure anomaly over same duration 302 thatincludes barometric ambient pressure spike 310 a may be identified, andspurious barometric pressure region 305 may be identified.

For comparison purposes, normal or nominal region 306 existing overduration of time 303, for instance, may depict ambient pressure increaseor spike 310 a caused by carried mobile device 101 changing floorswithin the building, in the case depicting an actual transition to alower floor, under relatively constant ambient temperature conditions301 b.

Methodology

FIG. 4 illustrates, in an example embodiment, a method of localizingmobile device 101 based on extreme ambient temperature conditions. Indescribing examples of FIG. 4, reference is made to the examples ofFIGS. 1-3 for purposes of illustrating suitable components or elementsfor performing a step or sub-step being described.

Examples of method steps described herein relate to the use of mobiledevice 101 for implementing the techniques described. According to oneembodiment, the techniques are performed by mobile device localizationlogic module 105 of mobile device 101 in response to the processor 201executing one or more sequences of software logic instructions thatconstitute mobile device localization logic module 105. In embodiments,mobile device localization logic module 105 may include the one or moresequences of instructions within sub-modules including temperatureanomaly detection module 210, anomaly confirmation module 211, ambientpressure filtering module 212 and barometric localization module 213.Such instructions may be read into memory 202 from machine-readablemedium, such as memory storage devices. In executing the sequences ofinstructions contained in temperature anomaly detection module 210,anomaly confirmation module 211, ambient pressure filtering module 212and barometric localization module 213 of mobile device localizationlogic module 105 in memory 202, processor 201 performs the process stepsdescribed herein. In alternative implementations, at least somehard-wired circuitry may be used in place of, or in combination with,the software logic instructions to implement examples described herein.Thus, the examples described herein are not limited to any particularcombination of hardware circuitry and software instructions.Additionally, it is contemplated that in alternative embodiments, thetechniques herein, or portions thereof, may be distributed between themobile device 101 and remote server computing device 107. For example,the mobile device may collect and transmit data to server 107 that, inturn, performs at least some portion of the techniques described herein.

At step 410, processor 201 executes instructions included in temperatureanomaly detection module 210, to detect, using one or more temperaturesensors of mobile device 101 operating at a first sampling rate, anambient temperature anomaly along indoor route 103 being traversed, suchas resulting from a building from a fire or high-temperature flames.

In embodiments, mobile device 101 barometric pressure data may include aset of barometric pressure measurements using one or more barometricpressure sensors of mobile device 101 while traversing a sequence ofpositions along route 103. Route 103 being traversed may be such as ahallway, a corridor, a pedestrian path, a set of stairs or a routecommencing from any of an entrance, an exit or a location within or neara given floor of a multi-floor building.

At step 420, processor 201 executes instructions included in anomalyconfirmation module 211 to determine, based on switching to a secondsampling rate of the temperature sensors of mobile device 101, that theambient temperature anomaly persists over a sequence of positions alongroute 103 being traversed. In one embodiment, the ambient temperaturesampling rate of temperature sensors of mobile device 101 may beswitched to operate at a higher frequency in order to confirm, withbetter certainty, the persistence of high-temperature flames within abuilding, for instance.

At step 430, processor 201 executes instructions included in ambientpressure filtering module 212 to filter a set of barometric ambientpressure measurements contemporaneously associated with the sequence ofpositions along route 103 during traversal, the by mobile device 101,the set of barometric ambient pressure measurements obtained using abarometric pressure sensor of the mobile device 101. In one embodiment,where the temperature anomaly that includes temperature spike 301 aexists over duration of time 302, a corresponding or contemporaneousbarometric pressure anomaly over same duration 302 that includesbarometric ambient pressure spike 310 a may be identified. Barometricambient pressure measurements of mobile device 101 may filter thebarometric ambient pressure anomaly. A threshold temperature may bepredetermined to define when an extreme condition temperature anomalyexists. For example, when the ambient temperature increases at a ratehigher than 3-5 degrees Celsius per minute, in one embodiment.

In one embodiment, the filtering constitutes disregarding ambientbarometric pressure changes as sensed by mobile device 101 for durationof time 302, as the latter may falsely indicate a height change or floorchange of mobile device 101 when in fact no such change occurred, butrather, the spike in ambient pressure as measured by mobile device 101resulting from presence and persistence of high-temperature flames orsimilar extreme ambient temperature anomaly. In this manner ofidentifying a given temperature anomaly along with its respectiveduration, barometric ambient pressure measurements contemporaneous withthat same duration are identified as spurious, disregarded, andtherefore not taken into account in localizing mobile device 101 to aparticular floor of a multi-floor building. In one embodiment, thefiltering at least partially discards pressure measurementscontemporaneous with a duration of the temperature anomaly that exceedsa predetermined threshold temperature for at least a portion of thesequence of positions. In yet another variation, the method may includealgorithmically smoothing the filtered set of barometric ambientpressure measurements, minimizing the effects of noise in the barometricpressure measurements, prior to localizing mobile device 101.

In embodiments, the data of repository 108 may be accessible in memory202 of mobile device 101, and also accessible from server computingdevice 107 via wireless communication network 106.

At step 440, processor 201 executes further instructions included inbarometric localization module 213 to localize mobile device 101 basedat least partly on matching the filtered set of barometric ambientpressure measurements with barometric fingerprint data of repository 108along route 103. In embodiments, the fingerprint map data stored infingerprint data repository 108 (also referred to herein as repository108) further associates unique positions along route 103 with anycombination of fingerprint data, including gyroscope data, magneticdata, accelerometer data, wireless signal strength data, wirelessconnectivity data, barometric data, acoustic data, line-of sight data,and ambient lighting data, in addition to barometric pressurefingerprint data stored thereon.

In one embodiment, the localizing identifies a floor number within themulti-floor facility. Erroneous elevation and floor estimationcalculations can result in life threatening circumstances forfirefighters in a burning building at least partially engulfed inflames. For example, if a firefighter climbed two flights of stairs witha smoke-filled atmosphere and then required assistance, and floorestimation calculations had been performed under an assumption that thefirefighter was surrounded by a nominal or normal atmosphere of air whenclimbing the stairs, the rescue crew would erroneously expect that thefirefighter had only climbed one flight of stairs instead of two, forinstance. For extreme fire conditions and associated significant changesin temperature and chemical composition of air due to heavy smoke,incremental height or elevation changes may be calculated, in oneembodiment, using a generalized hypsometric formula:

${\Delta \; h_{n}} = {\frac{R_{s}T_{kelvin}}{g}{\ln \left( \frac{P_{n - 1}}{P_{n}} \right)}}$

where T_(kelvin) is the instantaneous temperature in Kelvin, g isgravitational acceleration, P_(n) is the instantaneous pressure, P_(n-1)is a previous-instant pressure measurement, and R_(s) is the specificgas constant which may be estimated based on the gas sensor ambientreadings.

It is contemplated for embodiments described herein to extend toindividual elements and concepts described herein, independently ofother concepts, ideas or system, as well as for embodiments to includecombinations of elements recited anywhere in this application. Althoughembodiments are described in detail herein with reference to theaccompanying drawings, it is to be understood that the invention is notlimited to those precise embodiments. As such, many modifications andvariations will be apparent to practitioners skilled in this art.Accordingly, it is intended that the scope of the invention be definedby the following claims and their equivalents. Furthermore, it iscontemplated that a particular feature described either individually oras part of an embodiment can be combined with other individuallydescribed features, or parts of other embodiments, even if the otherfeatures and embodiments make no mention of the particular feature.Thus, the absence of describing combinations should not preclude theinventor from claiming rights to such combinations.

1. A method for localizing a mobile device having a processor and amemory, the method comprising: detecting, using a temperature sensor ofthe mobile device at a first sampling rate, an ambient temperatureanomaly along an indoor route within an indoor facility being traversed;filtering, based on the detecting, a set of barometric ambient pressuremeasurements contemporaneously associated with a sequence of positionsalong the indoor route, the set obtained using a barometric pressuresensor of the mobile device, the filtering based at least in part ondiscarding at least a portion of the set of barometric ambient pressuremeasurements; and localizing the mobile device based at least partly onthe filtered set of barometric ambient pressure measurements.
 2. Themethod of claim 1 wherein the method comprises determining, based onswitching to a second sampling rate, that the ambient temperatureanomaly persists over the sequence of positions along the indoor route,and wherein the filtering is performed, when it is determined that thethat the ambient temperature anomaly persists over the sequence ofpositions.
 3. The method of claim 1 wherein, when the indoor facility isa multi-floor facility, the localizing identifies a floor number withinthe multi-floor facility.
 4. The method of claim 1 wherein thelocalizing further comprises matching the filtered set of barometricambient pressure measurements with barometric fingerprint data of afingerprint data repository.
 5. The method of claim 4 wherein thefingerprint data repository is one of accessible in the memory andaccessible from a server computing device via a wireless communicationnetwork.
 6. The method of claim 4 wherein the fingerprint datarepository further includes at least one of wireless signal strengthdata, wireless connectivity data, accelerometer data, gyroscope data,magnetometer data and ambient lighting sensor data associated with therespective positions along the route.
 7. The method of claim 1 whereinthe set of barometric ambient pressure measurements is contemporaneouswith a duration of the temperature anomaly that exceeds a predeterminedthreshold temperature for at least a portion of the sequence ofpositions.
 8. The method of claim 8 wherein the second sampling ratecomprises a frequency that exceeds the first sampling rate.
 9. Themethod of claim 1 further comprising algorithmically smoothing thefiltered set of barometric ambient pressure measurements prior to thelocalizing.
 10. The method of claim 1 wherein the temperature anomaly isdetected when a rate of increase of temperature is greater than apredetermined rate.
 11. A mobile device comprising: a processor; amemory storing a set of instructions, the instructions executable in theprocessor to: detect, using a temperature sensor of the mobile device ata first sampling rate, an ambient temperature anomaly along an indoorroute being traversed; filter, based on the detecting, a set ofbarometric ambient pressure measurements contemporaneously associatedwith a sequence of positions along the indoor route, the set obtainedusing a barometric pressure sensor of the mobile device, the filteringbased at least in part on discarding at least a portion of the set ofbarometric ambient pressure measurements; and localize the mobile devicebased at least partly on the filtered set of barometric ambient pressuremeasurements.
 12. The mobile device of claim 11 wherein the processor isto determine, based on switching to a second sampling rate, that theambient temperature anomaly persists over the sequence of positionsalong the indoor route, and wherein the filtering is performed, when itis determined that the that the ambient temperature anomaly persistsover the sequence of positions.
 13. The mobile device of claim 11wherein, when the indoor facility is a multi-floor facility, thelocalizing identifies a floor number within the multi-floor facility.14. The mobile device of claim 11 wherein the localizing furthercomprises matching the filtered set of barometric ambient pressuremeasurements with barometric fingerprint data of a fingerprint datarepository.
 15. The mobile device of claim 14 wherein the fingerprintdata repository is one of accessible in the memory and accessible from aserver computing device via a wireless communication network.
 16. Themobile device of claim 14 wherein the fingerprint data repositoryfurther includes at least one of wireless signal strength data, wirelessconnectivity data, accelerometer data, gyroscope data, magnetometer dataand ambient lighting sensor data associated with the respectivepositions along the route.
 17. The mobile device of claim 11 wherein theset of barometric ambient pressure measurements is contemporaneous witha duration of the temperature anomaly that exceeds a predeterminedthreshold temperature for at least a portion of the sequence ofpositions.
 18. The mobile device of claim 18 wherein the second samplingrate comprises a frequency that exceeds the first sampling rate.
 19. Themobile device of claim 11 further comprising instructions executable inthe processor to algorithmically smooth the filtered set of barometricambient pressure measurements prior to the localizing.
 20. The mobiledevice of claim 11 wherein the temperature anomaly is detected when arate of increase of temperature is greater than a predetermined rate.